PREDICTIVE PERFORMANCE AND CLINICAL UTILITY OF A NEW PREDICTIVE MODEL OF CARDIOVASCULAR RISK FOR YOUNG AND MIDDLE-AGED WORKING POPULATION. (June 2018)

• Record Type: Journal Article
• Authors: Ruilope, L.M.; Fernández-Labandera, C.; Quevedo-Aguado, L.; Catalina-Romero, C.; Martínez-Muñoz, P.; Valdivielso-Felices, P.; Sánchez-Chaparro, M.A.; Calvo-Bonacho, E.
• Is Part Of: Journal of hypertension. Volume 36(2018)Supplement 1
• Publication Date: 2018-06
• Subjects: Hypertension -- Periodicals; Hypertension -- Periodicals; 616.132005
• DOI: 10.1097/01.hjh.0000539624.20457.e0
• Languages: English
• ISSNs: 1473-5598

Abstract

Abstract : Objective: Identifying people at high cardiovascular risk is challenging, especially at young age. The main objective of the IberScore study was to derive a mathematical model for risk prediction of fatal and non-fatal cardiovascular events from a relatively young and healthy working population. Design and method: A predictive function for fatal and non-fatal CV events was derived from a cohort of 774, 404 workers (70.4% of the target population), free of CV disease at entry, who were followed during 10 years. Workers ages ranged 16–65 years (mean 35.7, SD 10.7). 71.7% were men, which represented the real proportion in the target population. Cardiovascular ageing was estimated (independently by genders) based on the effects of well-known cardiovascular risk factors as: smoking; cholesterol; blood glucose; HDL; systolic blood pressure (SBP); obesity; history of dyslipidemia, diabetes and hypertension. Results: Along the 10-year follow-up we found 3, 762 first cardiovascular events (6‰) in derivation cohort. Most of them (80.3%) were non-fatal ischemic events. We derived a logistic flexible parametric model to predict 10-year cardiovascular risk. 82% of those who suffered a cardiovascular event during the follow-up span had been previously classified as "high risk" or "very high risk" using our model, whereas only 12% of them were classified in the same groups using SCORE. The latter also showed a weak discrimination power for risk stratification while IberScore clearly distinguished the four risk categories. IberScore was well calibrated and showed outstanding predictive performance and clinical utility even at young and middle-age workers. Cut-off points were fixed taking on account their discriminatory capacity and the balance between costs and benefits of the treatments that will be prescribed based on them. Conclusions: IberScore worked much better to estimate cardiovascular risk in a relatively young and healthy Spanish working population when compared to other models. Cardiovascular aging, as the result of the effects of risk factors, should be at the core of CV risk estimation. Cut-off points should be set considering the benefit we seek with the treatments we have in mind.